Robot Navigation in Unseen Spaces using an Abstract Map

Human navigation in built environments depends on symbolic spatial information which has unrealised potential to enhance robot navigation capabilities. Information sources such as labels, signs, maps, planners, spoken directions, and navigational gestures communicate a wealth of spatial information to the navigators of built environments; a wealth of information that robots typically ignore. We present a robot navigation system that uses the same symbolic spatial information employed by humans to purposefully navigate in unseen built environments with a level of performance comparable to humans. The navigation system uses a novel data structure called the abstract map to imagine malleable spatial models for unseen spaces from spatial symbols. Sensorimotor perceptions from a robot are then employed to provide purposeful navigation to symbolic goal locations in the unseen environment. We show how a dynamic system can be used to create malleable spatial models for the abstract map, and provide an open source implementation to encourage future work in the area of symbolic navigation. Symbolic navigation performance of humans and a robot is evaluated in a real-world built environment. The paper concludes with a qualitative analysis of human navigation strategies, providing further insights into how the symbolic navigation capabilities of robots in unseen built environments can be improved in the future.Comment: 15 pages, published in IEEE Transactions on Cognitive and Developmental Systems (http://doi.org/10.1109/TCDS.2020.2993855), see https://btalb.github.io/abstract_map/ for access to softwar

The real-time learning mechanism of the Scientific Research Associates Advanced Robotic System (SRAARS)

Scientific research associates advanced robotic system (SRAARS) is an intelligent robotic system which has autonomous learning capability in geometric reasoning. The system is equipped with one global intelligence center (GIC) and eight local intelligence centers (LICs). It controls mainly sixteen links with fourteen active joints, which constitute two articulated arms, an extensible lower body, a vision system with two CCD cameras and a mobile base. The on-board knowledge-based system supports the learning controller with model representations of both the robot and the working environment. By consecutive verifying and planning procedures, hypothesis-and-test routines and learning-by-analogy paradigm, the system would autonomously build up its own understanding of the relationship between itself (i.e., the robot) and the focused environment for the purposes of collision avoidance, motion analysis and object manipulation. The intelligence of SRAARS presents a valuable technical advantage to implement robotic systems for space exploration and space station operations

Towards an Indexical Model of Situated Language Comprehension for Cognitive Agents in Physical Worlds

We propose a computational model of situated language comprehension based on the Indexical Hypothesis that generates meaning representations by translating amodal linguistic symbols to modal representations of beliefs, knowledge, and experience external to the linguistic system. This Indexical Model incorporates multiple information sources, including perceptions, domain knowledge, and short-term and long-term experiences during comprehension. We show that exploiting diverse information sources can alleviate ambiguities that arise from contextual use of underspecific referring expressions and unexpressed argument alternations of verbs. The model is being used to support linguistic interactions in Rosie, an agent implemented in Soar that learns from instruction.Comment: Advances in Cognitive Systems 3 (2014

Emergence of technostress among employees working with physical robots

Despite the growing body of literature on technostress, there is limited knowledge about the emergence of technostress among people working with physical robots. In this paper, we aim to address this research gap by exploring how technostress emerges among employees working with physical robots. The study was based on qualitative online questionnaire responses from 199 present or previous users of robots at work. Based on our data, we identified several robot-related environmental conditions that contributed to perceived work-related stress. In addition, we identified personal and situational factors that influenced perceived stress. Our findings reveal that the emergence of technostress among employees working with physical robots has distinct characteristics, and that the technostressors identified in previous studies are insufficient for explaining stress in this context. Therefore, our study extends the technostress literature and provides insights into employees’ experiences in organizations that use physical robots

The Mechanics of Embodiment: A Dialogue on Embodiment and Computational Modeling

Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamouring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensory-motor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialogue between two fictional characters: Ernest, the �experimenter�, and Mary, the �computational modeller�. The dialogue consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and, conversely, the impact that computational modeling could have on embodied theories. The second part of the article discusses the most important open challenges for embodied computational modelling

How Does Robotic Surgery Influence Communication, Leadership, and Team Outcomes? A Multimethod Examination.

The practice of delivering surgical care has evolved to be less invasive to the patients undergoing surgery. Minimally-invasive surgery can be practiced through traditional laparoscopic methods as well as with robotic technology that displaces the surgeon from the operating table. Robotic surgery has been cited to be safer and more effective than traditional laparoscopic surgery; however, little research has endeavored to investigate the role of surgical modality upon aspects of teamwork. This dissertation contributes to the human factors and teamwork literature by evaluating how surgical modality may influence communication, shared leadership, and team outcomes. Multiple methods were employed to study robotic and non-robotic (i.e., open and laparoscopic) surgical teams. Teams were evaluated through video analysis of surgical procedures as well as questionnaire methods. The results of this research revealed very few modality-specific differences which may represent the adaptive nature of teams and individuals. Robotic surgical team members did not perceive a statistically significant difference in communication quality which may indicate that the impact of the closed console design may be relatively benign in this regard. While there were no statistically significant differences between the degree to which robotic and non-robotic teams shared or perceived shared leadership, there were interesting role and leadership behavior type differences. For instance, the assists conducted significantly more leadership in robotic surgery than in laparoscopic surgery. In the video data, sharing leadership to a greater extent led to shorter operative durations. In the survey data, higher perceptions of communication quality and communication behavior significantly predicted higher perceptions of team effectiveness, indicating a strong positive relationship between perceived communication and perceived effectiveness. As robotic surgical systems and practices continue to inevitably advance in the coming years, developers should be keenly aware of the interdependencies between all aspects of the sociotechnical system including the providers and recipients of care, the environment and organization, and the tools and technologies

Shopping centres revisited: exploring new attributes of attractiveness

Traditional retailing is facing tough challenges, driven not least by the trend towards online shopping. This paper revisits shopping centres research in light of the recent increasing role of technologies, leisure activities and changes in consumer behaviour. Drawing upon 10,544 consumers’ unsolicited communications on Twitter relating to the 19 main shopping centres in UK that were posted in May 2019, this research seeks to understand how retail attributes are unevenly distributed across consumers’ evaluations to define the attributes driving consumers’ evaluations of retail-leisure complexes. Results demonstrate the impact of each identified attribute on preferences for retail-leisure complexes. In particular, findings provide important insights for scholars and practitioners related to the design of future attractive shopping centres. Shopping centres can play an important role in contributing to the viability and vitality of towns. We consider the findings in the light of wider policy and regulatory debates

Learning cognitive maps: Finding useful structure in an uncertain world

In this chapter we will describe the central mechanisms that influence how people learn about large-scale space. We will focus particularly on how these mechanisms enable people to effectively cope with both the uncertainty inherent in a constantly changing world and also with the high information content of natural environments. The major lessons are that humans get by with a less is more approach to building structure, and that they are able to quickly adapt to environmental changes thanks to a range of general purpose mechanisms. By looking at abstract principles, instead of concrete implementation details, it is shown that the study of human learning can provide valuable lessons for robotics. Finally, these issues are discussed in the context of an implementation on a mobile robot. © 2007 Springer-Verlag Berlin Heidelberg